Search Results (1,086)

Background: Varicella remains a prevalent vaccine-preventable disease, but breakthrough infections are increasingly reported. However, long-term, population-based studies investigating the temporal and demographic characteristics of breakthrough varicella remain limited. Methods: This retrospective study analyzed surveillance data from Jinhua City, China, from 2016 to 2024. Varicella case records were obtained from the China Information System for Disease Control and Prevention (CISDCP), while vaccination data were retrieved from the Zhejiang Provincial Immunization Program Information System (ISIS). Breakthrough cases were defined as infections occurring more than 42 days after administration of the varicella vaccine. Differences in breakthrough interval were analyzed across subgroups defined by dose, sex, age, population category, and vaccination type. A bivariate cubic regression model was used to assess the combined effect of initial vaccination age and dose interval on the breakthrough interval. Results: Among 28,778 reported varicella cases, 7373 (25.62%) were classified as breakthrough infections, with a significant upward trend over the 9-year period (p < 0.001). Most cases occurred in school-aged children, especially those aged 6–15 years. One-dose recipients consistently showed shorter breakthrough intervals than two-dose recipients (M = 62.10 vs. 120.10 months, p < 0.001). Breakthrough intervals also differed significantly by sex, age group, population category, and vaccination type (p < 0.05). Regression analysis revealed a negative correlation between the initial vaccination age, the dose interval, and the breakthrough interval (R² = 0.964, p < 0.001), with earlier and closely spaced vaccinations associated with longer protection. Conclusions: The present study demonstrates that a two-dose varicella vaccination schedule, when initiated at an earlier age and administered with a shorter interval between doses, provides more robust and longer-lasting protection. These results offer strong support for incorporating varicella vaccination into China’s National Immunization Program to enhance vaccine coverage and reduce the public health burden associated with breakthrough infections. Full article

Variable-thrust liquid rocket engines are essential for precision landing in deep-space exploration, reusable launch vehicle recovery, high-accuracy orbital maneuvers, and emergency obstacle evasions of space drones. However, with the increasingly complex space missions, challenges remain with the development of different technical schemes. In view of these issues, this paper systematically reviews the technology’s evolution through mechanical throttling, electromechanical precision regulation, and commercial space-driven deep throttling. Then, the development of key variable thrust technologies for liquid rocket engines is summarized from the perspective of thrust regulation and control strategy. For instance, thrust regulation requires synergistic flow control devices and adjustable pintle injectors to dynamically match flow rates with injection pressure drops, ensuring combustion stability across wide thrust ranges—particularly under extreme conditions during space drones’ high-maneuver orbital adjustments—though pintle injector optimization for such scenarios remains challenging. System control must address strong multivariable coupling, response delays, and high-disturbance environments, as well as bottlenecks in sensor reliability and nonlinear modeling. Furthermore, prospects are made in response to the research progress, and breakthroughs are required in cryogenic wide-range flow regulation for liquid oxygen-methane propellants, combustion stability during deep throttling, and AI-based intelligent control to support space drones’ autonomous orbital transfer, rapid reusability, and on-demand trajectory correction in complex deep-space missions. Full article

The operation of heavy-haul railway trains with large loads results in significant cracking issues in reinforced concrete beams. Atmospheric carbon dioxide, oxygen, and moisture from the atmosphere penetrate into the beam interior through these cracks, accelerating the carbonation of the concrete and the corrosion of the steel bars. The rust-induced expansion of steel bars further exacerbates the cracking of the beam. The interaction between environmental factors and beam cracks leads to a rapid decline in the durability of the beam. To address this issue, a multi-physics field coupling durability assessment method was proposed, considering concrete beam cracking, concrete carbonation, and steel bar corrosion. The interaction among these three factors is achieved through sequential coupling, using crack width, carbonation passivation time, and steel bar corrosion rate as interaction parameters. Using this method, the deterioration morphology and stiffness degradation laws of 8 m reinforced concrete beams under different load conditions, including those of heavy and light trains in heavy-haul railways, are compared and assessed. The analysis reveals that within a 100-year service cycle, the maximum relative stiffness reduction for beams on the heavy train line is 20.0%, whereas for the light train line, it is only 7.4%. The degree of structural stiffness degradation is closely related to operational load levels, and beam cracking plays a critical role in this difference. Full article

Industrial building renovation is a sustainable strategy to preserve urban heritage while meeting modern needs. However, how interior material scenes affect users’ emotions, thermal perception, and functional preferences remains underexplored in adaptive reuse contexts. This study used virtual reality (VR) to examine four common material scenes—wood, concrete, red brick, and white-painted surfaces—within industrial renovation settings. A total of 159 participants experienced four Lumion-rendered VR environments and rated them on thermal perception (visual warmth, thermal sensation, comfort), emotional response (arousal, pleasure, restoration), and functional preference. Data were analyzed using repeated measures ANOVA and Pearson correlation. Wood and red brick scenes were associated with warm visuals; wood scenes received the highest ratings for thermal comfort and pleasure, white-painted scenes for restoration and arousal, and concrete scenes, the lowest scores overall. Functional preferences varied by space: white-painted and concrete scenes were most preferred in study/work settings, wood in social spaces, wood and red brick in rest areas, and concrete in exhibition spaces. By isolating material variables in VR, this study offers a novel empirical approach and practical guidance for material selection in adaptive reuse to enhance user comfort, emotional well-being, and spatial functionality in industrial heritage renovations. Full article

Background/Objectives: Porcine circovirus type 2 (PCV2) infection causes porcine circovirus disease (PCVD), a global immunosuppressive disease in pigs. Its clinical manifestations include post-weaning multisystemic wasting syndrome (PMWS) and porcine dermatitis and nephropathy syndrome (PDNS), which cause significant economic losses to the swine industry. The Cap protein, which is the major protective antigen of PCV2, can self-assemble to form virus-like particles (VLPs) in the insect baculovirus expression system. Few studies have compared the expression of Cap proteins in different baculovirus expression systems. Methods: In this study, we compared two commonly commercialized baculovirus construction systems with the Cap protein expression in various insect cells. Results: The results demonstrate that the flashBAC system expressed the Cap protein at higher levels than the Bac-to-Bac system. Notably, when expressing four copies of the Cap protein, the flashBAC system achieved the highest protein yield in High Five cells, where it reached 432 μg/mL at 5 days post-infection (dpi) with 27 °C cultivation. Animal experiments confirmed that the purified Cap protein effectively induced specific antibody production in mice and swine. Conclusions: This study provides critical data for optimizing the production of the PCV2 Cap protein, which is of great significance for reducing the production cost of PCV2 vaccines and improving the industrial production efficiency. Full article

Cadmium (Cd)-induced pulmonary toxicity is closely associated with ferroptosis, a regulated form of cell death characterized by iron-dependent lipid peroxidation (LPO). Luteolin (Lut) is a natural flavonoid compound that exists in many plants. In this study, we used human bronchial epithelial BEAS-2B cells to explore the impact of ferroptosis in the inhibition of Cd-induced BEAS-2B cells proliferation. BEAS-2B cells were exposed to Cd (5 μM) with/without Lut (10 μM), ferroptosis modulators (Ferrostatin-1 (Fer-1)/Erastin), or nuclear factor erythroid 2-related factor 2 (Nrf2) regulators (tert-butylhydroquinone (TBHQ)/ML385). Viability, iron content, reactive oxygen species (ROS), LPO, mitochondrial membrane potential (MMP), and glutathione peroxidase (GSH-PX) activity were assessed. Exposure to Cd significantly decreased cell viability, increased intracellular iron levels, ROS production, and LPO activity, while simultaneously reducing MMP and GSH-PX activity. Fer-1 mitigated Cd-induced cytotoxicity, but Erastin intensified these effects. Mechanistically, Cd exposure suppressed the Nrf2/Solute Carrier Family 7 Member 11 (SLC7A11)/glutathione peroxidase 4 (GPX4) signaling pathway, which plays a crucial role in maintaining redox homeostasis. Activation of Nrf2 using TBHQ mitigated oxidative stress and upregulated the expression of key proteins within this pathway, while inhibition of Nrf2 with ML385 exacerbated cellular damage. Notably, Lut treatment could significantly alleviate Cd-induced cytotoxicity, oxidative stress, and downregulation of Nrf2/SLC7A11/GPX4 proteins. These findings demonstrate that ferroptosis is a critical mechanism underlying Cd-mediated lung epithelial injury and identify Lut as a promising therapeutic candidate via its activation of Nrf2-driven antioxidant defense mechanisms. This study provides novel insights into molecular targets for the prevention and treatment of Cd-associated pulmonary disorders. Full article

Synthetic aperture radar images can be used for ship target detection. However, due to the unclear ship outline in SAR images, noise and land background factors affect the difficulty and accuracy of ship (especially small target ship) detection. Therefore, based on the YOLOv5s model, this paper improves its backbone network and feature fusion network algorithm to improve the accuracy of ship detection target recognition. First, the LSKModule is used to improve the backbone network of YOLOv5s. By adaptively aggregating the features extracted by large-size convolution kernels to fully obtain context information, at the same time, key features are enhanced and noise interference is suppressed. Secondly, multiple Depthwise Separable Convolution layers are added to the SPPF (Spatial Pyramid Pooling-Fast) structure. Although a small number of parameters and calculations are introduced, features of different receptive fields can be extracted. Third, the feature fusion network of YOLOv5s is improved based on BIFPN, and the shallow feature map is used to optimize the small target detection performance. Finally, the CoordConv module is added before the detect head of YOLOv5, and two coordinate channels are added during the convolution operation to further improve the accuracy of target detection. The map50 of this method for the SSDD dataset and HRSID dataset reached 97.6% and 91.7%, respectively, and was compared with a variety of advanced target detection models. The results show that the detection accuracy of this method is higher than other similar target detection algorithms. Full article

The sheaths of bamboo shoots, characterized by distinct colors and spotting patterns, are key phenotypic markers influencing species classification, market value, and genetic studies. This study introduces YOLOv8-BS, a deep learning model optimized for detecting these traits in Chimonobambusa utilis using a dataset from Jinfo Mountain, China. Enhanced by data augmentation techniques, including translation, flipping, and contrast adjustment, YOLOv8-BS outperformed benchmark models (YOLOv7, YOLOv5, YOLOX, and Faster R-CNN) in color and spot detection. For color detection, it achieved a precision of 85.9%, a recall of 83.4%, an F1-score of 84.6%, and an average precision (AP) of 86.8%. For spot detection, it recorded a precision of 90.1%, a recall of 92.5%, an F1-score of 91.1%, and an AP of 96.1%. These results demonstrate superior accuracy and robustness, enabling precise phenotypic analysis for bamboo germplasm evaluation and genetic diversity studies. YOLOv8-BS supports precision agriculture by providing a scalable tool for sustainable bamboo-based industries. Future improvements could enhance model adaptability for fine-grained varietal differences and real-time applications. Full article

The Alpine Periglacial Weathering Zone (APWZ) is a critical transitional belt between alpine vegetation and glaciers, and a highly sensitive region to climate change. Its dynamic variations profoundly reflect the surface environment’s response to climatic shifts. Taking Gongga Mountain as the study area, this study utilizes summer Landsat imagery from 1986 to 2024 and constructs a remote sensing method based on NDVI and NDSI indices using the Otsu thresholding algorithm on the Google Earth Engine platform to automatically extract the positions of the upper limit of vegetation and the snowline. Results show that over the past four decades, the APWZ in Gongga Mountain has exhibited a continuous upward shift, with the mean elevation rising from 4101 m to 4575 m. The upper limit of vegetation advanced at an average rate of 17.43 m/a, significantly faster than the snowline shift (3.9 m/a). The APWZ also experienced substantial areal shrinkage, with an average annual reduction of approximately 13.84 km², highlighting the differential responses of various surface cover types to warming. Spatially, the most pronounced changes occurred in high-elevation zones (4200–4700 m), moderate slopes (25–33°), and sun-facing aspects (east, southeast, and south slopes), reflecting a typical climate–topography coupled driving mechanism. In the upper APWZ, glacier retreat has intensified weathering and increased debris accumulation, while the newly formed vegetation zone in the lower APWZ remains structurally fragile and unstable. Under extreme climatic disturbances, this setting is prone to triggering chain-type hazards such as landslides and debris flows. These findings enhance our capacity to monitor alpine ecological boundary changes and identify associated disaster risks, providing scientific support for managing climate-sensitive mountainous regions. Full article

The thermal environment problem is one of the main focuses of current urban environment research. At present, there are various methods used in urban space thermal environment (USTE) research. As a simulation method to quantify the USTE, the urban weather generator (UWG) has undergone great development and achieved many progressive results. It is necessary to establish and review its current research status by synthesizing UWG multi-scale applications. This review adopts a literature review approach, leveraging the Web of Science Core Collection to obtain previous relevant publications from 2010 to 2025 using “urban weather generator” and “thermal environment” as keywords. The literature is categorized by research themes, including model development, parameter optimization, and application cases. Through innovative analyses of spatio-temporal-scale classification, parameter optimization, the integration of anthropogenic heat emissions, and the multi-domain simulation potential of the UWG, this review synthesizes the application outcomes of the UWG model in multi-scale research, addressing gaps in current urban climate studies. The paper aims to elaborate and analyze the model’s current research status considering the following six aspects. First, the basic parameters in UWG simulation are introduced, including the data and parameter determination settings used in such simulations. Secondly, we introduce the simulation model and its basic principles, the simulation process, and the main steps of this process. Third, we classify and define UWG simulations of spatial thermal environments at different time scales and spatial scales. Fourth, regarding how to improve the accuracy of the UWG model, the deterministic parameters and uncertainty parameters settings are analyzed, respectively. Then, the impacts of anthropogenic heat during the simulation process are also discussed. Fifth, the applications of the UWG model in some major fields and its possible future development directions are addressed. Finally, the existing problems are summarized, the future development trends are prospected, and research on possible expected mitigation measures for the USTE is described. Full article

This study aimed to investigate the effects of adding 360 mg/kg niacinamide (NAM) to diets on nutrient metabolism, providing insights into how dietary NAM supplementation enhances nitrogen utilization and growth performance in pigs. Forty growing–finishing pigs were randomly assigned to one of four experimental diets as follows: basal diet + 30 mg/kg NAM (CON), basal diet + 360 mg/kg NAM (CON + NAM), low-protein diet + 30 mg/kg NAM (LP), and low-protein diet + 360 mg/kg NAM (LP + NAM). Results showed that supplementation of both the CON and LP diets with 360 mg/kg NAM resulted in decreased urea nitrogen concentrations and carbamyl phosphate synthetase-I activity (p < 0.05). The pyruvate dehydrogenase activity in the serum and liver, as well as the activity of pyruvate dehydrogenase, citrate synthase, and glutamate dehydrogenase 1 in the ileum mucosa, was increased by supplementing the LP diet with 360 mg/kg NAM (p < 0.05). The LP diet with 360 mg/kg NAM increased the villi length to crypt depth, mRNA expression of glucose transporters 1 and 2 and alanine-serine-cysteine transporter 1, and mRNA expression of mechanistic target of the rapamycin 1 in the ileum (p < 0.05). Additionally, 360 mg/kg NAM supplementation in the LP diet reduced ileal Lactobacillus abundance (LDA > 4) and increased ileal microbial nucleotide and purine metabolism (p < 0.05). Our findings suggest that addition of 360 mg/kg NAM to the LP diet reduced urea production in the liver, enhanced glucose and amino acid absorption and transport in the ileum, and improved glucose metabolism. Full article

Halloysite nanotubes, a naturally occurring nanomaterial with a unique tubular morphology, have shown considerable potential for heavy metal remediation. However, significant inconsistencies in the reported maximum adsorption capacities (q_max) for heavy metal ions—such as Pb²⁺, which ranges from 7.5 to 84.0 mg/g with a coefficient of variation (CV) of 68%—have severely hindered both scientific understanding and practical application of this promising material. To address this critical knowledge gap, we conducted a reassessment using carefully selected halloysite specimens from three geologically distinct deposits (Utah, USA; Henan and Yunnan, China). Under rigorously controlled experimental conditions, we precisely quantified the adsorption capacities of halloysite for Cd²⁺, Zn²⁺, and Pb²⁺. Through an integrated multi-technique characterization approach involving XRF, XRD, FTIR, TEM, and BET analyses, we identified two fundamental crystallochemical parameters that govern the adsorption performance of halloysite: the degree of lattice substitution and the density of surface hydroxyl groups. Our findings reveal that optimal heavy metal adsorption occurs in halloysite with lower lattice substitution and higher surface hydroxyl density. This work not only provides a reliable range of adsorption capacities for halloysite but, more importantly, establishes a scientific foundation for optimizing the application of halloysite in heavy metal remediation. Full article

Various approaches have been explored to address the path planning problem for mobile robots. However, it remains a significant challenge, particularly in environments where a multi-tasking mobile robot operates alongside stochastically moving humans. This paper focuses on path planning for a mobile robot executing multiple pickup and delivery tasks in an environment shared with humans. To plan a safe path and achieve high task success rate, a Reinforcement Learning (RL)-based double layer controller is proposed in which a double-layer learning algorithm is developed. The high-level layer integrates a Finite-State Automaton (FSA) with RL to perform global strategy learning and task-level decision-making. The low-level layer handles local path planning by incorporating a Markov Decision Process (MDP) that accounts for environmental uncertainties. We verify the proposed double layer algorithm under different configurations and evaluate its performance based on several metrics, including task success rate, reward, etc. The proposed method outperforms conventional RL in terms of reward (+63.1%) and task success rate (+113.0%). The simulation results demonstrate the effectiveness of the proposed algorithm in solving path planning problem with stochastic human uncertainties. Full article

Multi-stage fractured horizontal wells (MSFHWs) represent a crucial development approach for low-permeability reservoirs, where accurate productivity prediction is essential for production operations. However, existing models suffer from limitations such as inadequate characterization of complex flow mechanisms within the reservoir or computational complexity. This study subdivides the flow process into three segments: matrix, fracture, and wellbore. By employing discretization concepts, potential distribution theory, and the principle of potential superposition, a productivity prediction model tailored for MSFHWs in low-permeability reservoirs is established. Moreover, this model provides a clearer characterization of fluid seepage processes during horizontal well production, which aligns more closely with the actual production process. Validated against actual production data from an offshore oilfield and benchmarked against classical models, the proposed model demonstrates satisfactory accuracy and reliability. Sensitivity analysis reveals that a lower Threshold Pressure Gradient (TPG) corresponds to higher productivity; a production pressure differential of 10 MPa yields an average increase of 22.41 m³/d in overall daily oil production compared to 5 MPa, concurrently reducing the overall production decline rate by 26.59% on average. Larger stress-sensitive coefficients lead to reduced production, with the fracture stress-sensitive coefficient exerting a more significant influence; for an equivalent increment, the matrix stress-sensitive coefficient causes a production decrease of 1.92 m³/d (a 4.32% decline), while the fracture stress-sensitive coefficient results in a decrease of 4.87 m³/d (a 20.93% decline). Increased fracture half-length and number enhance production, with an initial productivity increase of 21.61% (gradually diminishing to 7.1%) for longer fracture half-lengths and 24.63% (gradually diminishing to 5.22%) for more fractures; optimal critical values exist for both parameters. Full article

Ubiquitination is a dynamic and reversible post-translational modification mediated by ubiquitination regulators (UBRs), which plays an essential role in protein stability, cell differentiation and immunity. Dysregulation of UBRs can lead to destabilization of biological processes and may induce serious human diseases, including cancer. Many UBRs, such as E3 ubiquitin ligases and deubiquitinases (DUBs), have been identified as potential drug targets for cancer therapy. However, the potential clinical value of UBRs in lung adenocarcinoma (LUAD) remains to be elucidated. Here, we identified 17 hub UBRs from high-confidence protein–protein interaction networks of UBRs correlated with cancer hallmark-related pathways using four topological algorithms. The expression of hub UBRs is affected by copy number variation and post-transcriptional regulation, and their high expression is often detrimental to patient survival. Based on the expression profiles of hub UBRs, patients can be classified into two ubiquitination subtypes with different characteristics. These subtypes exhibit significant differences across multiple dimensions, including survival, expression level, mutation burden, female predominance, infiltration level, immune profile, and drug response. In addition, we established a scoring system for evaluating the ubiquitination status of individual LUAD patients, called the ubiquitination-related risk (UB_risk) score, and found that patients with low scores are more likely to gain advantages from immunotherapy. The results of this study emphasize the critical role of ubiquitination in the classification, tumor microenvironment and immunotherapy of LUAD. The construction of the UB_risk scoring system lays a research foundation for evaluating the ubiquitination status of individual LUAD patients and formulating precise treatment strategies from the ubiquitination level. Full article